Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

ABSTRACT: Accelerating the drug discovery process requires predictive computational protocols capable of reducing or simplifying the synthetic and/or combinatorial challenge. Docking-based virtual screening methods have been developed and successfully applied to a number of pharmaceutical targets. In this review, we first present the current status of docking and scoring methods, with exhaustive lists of these. We next discuss reported comparative studies, outlining criteria for their interpretation. In the final section, we describe some of the remaining developments that would potentially lead to a universally applicable docking/scoring method.

SUBMITTER: Moitessier N

PROVIDER: S-EPMC2268060 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Moitessier N N Englebienne P P Lee D D Lawandi J J Corbeil C R CR

British journal of pharmacology 20071126

Accelerating the drug discovery process requires predictive computational protocols capable of reducing or simplifying the synthetic and/or combinatorial challenge. Docking-based virtual screening methods have been developed and successfully applied to a number of pharmaceutical targets. In this review, we first present the current status of docking and scoring methods, with exhaustive lists of these. We next discuss reported comparative studies, outlining criteria for their interpretation. In t ...[more]

PMID: 18037925

Similar Datasets

An efficient and accurate molecular alignment and docking technique using ab initio quality scoring.

Project description:An accurate and efficient molecular alignment technique is presented based on first principle electronic structure calculations. This new scheme maximizes quantum similarity matrices in the relative orientation of the molecules and uses Fourier transform techniques for two purposes. First, building up the numerical representation of true ab initio electronic densities and their Coulomb potentials is accelerated by the previously described Fourier transform Coulomb method. Second, the Fourier convolution technique is applied for accelerating optimizations in the translational coordinates. In order to avoid any interpolation error, the necessary analytical formulas are derived for the transformation of the ab initio wavefunctions in rotational coordinates. The results of our first implementation for a small test set are analyzed in detail and compared with published results of the literature. A new way of refinement of existing shape based alignments is also proposed by using Fourier convolutions of ab initio or other approximate electron densities. This new alignment technique is generally applicable for overlap, Coulomb, kinetic energy, etc., quantum similarity measures and can be extended to a genuine docking solution with ab initio scoring.

| S-EPMC2669769 | biostudies-other

Four-dimensional docking: a fast and accurate account of discrete receptor flexibility in ligand docking.

Project description:Many available methods aimed at incorporating the receptor flexibility in ligand docking are computationally expensive, require a high level of user intervention, and were tested only on benchmarks of limited size and diversity. Here we describe the four-dimensional (4D) docking approach that allows seamless incorporation of receptor conformational ensembles in a single docking simulation and reduces the sampling time while preserving the accuracy of traditional ensemble docking. The approach was tested on a benchmark of 99 therapeutically relevant proteins and 300 diverse ligands (half of them experimental or marketed drugs). The conformational variability of the binding pockets was represented by the available crystallographic data, with the total of 1113 receptor structures. The 4D docking method reproduced the correct ligand binding geometry in 77.3% of the benchmark cases, matching the success rate of the traditional approach but employed on average only one-fourth of the time during the ligand sampling phase.

| S-EPMC2662720 | biostudies-literature

DrugScorePPI webserver: fast and accurate in silico alanine scanning for scoring protein-protein interactions.

Project description:Protein-protein complexes play key roles in all cellular signal transduction processes. We have developed a fast and accurate computational approach to predict changes in the binding free energy upon alanine mutations in protein-protein interfaces. The approach is based on a knowledge-based scoring function, DrugScore(PPI), for which pair potentials were derived from 851 complex structures and adapted against 309 experimental alanine scanning results. Based on this approach, we developed the DrugScore(PPI) webserver. The input consists of a protein-protein complex structure; the output is a summary table and bar plot of binding free energy differences for wild-type residue-to-Ala mutations. The results of the analysis are mapped on the protein-protein complex structure and visualized using J mol. A single interface can be analyzed within a few minutes. Our approach has been successfully validated by application to an external test set of 22 alanine mutations in the interface of Ras/RalGDS. The DrugScore(PPI) webserver is primarily intended for identifying hotspot residues in protein-protein interfaces, which provides valuable information for guiding biological experiments and in the development of protein-protein interaction modulators. The DrugScore(PPI) Webserver, accessible at http://cpclab.uni-duesseldorf.de/dsppi, is free and open to all users with no login requirement.

| S-EPMC2896140 | biostudies-literature

VORFFIP-driven dock: V-D2OCK, a fast and accurate protein docking strategy.

Project description:The experimental determination of the structure of protein complexes cannot keep pace with the generation of interactomic data, hence resulting in an ever-expanding gap. As the structural details of protein complexes are central to a full understanding of the function and dynamics of the cell machinery, alternative strategies are needed to circumvent the bottleneck in structure determination. Computational protein docking is a valid and valuable approach to model the structure of protein complexes. In this work, we describe a novel computational strategy to predict the structure of protein complexes based on data-driven docking: VORFFIP-driven dock (V-D2OCK). This new approach makes use of our newly described method to predict functional sites in protein structures, VORFFIP, to define the region to be sampled during docking and structural clustering to reduce the number of models to be examined by users. V-D2OCK has been benchmarked using a validated and diverse set of protein complexes and compared to a state-of-art docking method. The speed and accuracy compared to contemporary tools justifies the potential use of VD2OCK for high-throughput, genome-wide, protein docking. Finally, we have developed a web interface that allows users to browser and visualize V-D2OCK predictions from the convenience of their web-browsers.

| S-EPMC4357426 | biostudies-literature

Activity fingerprinting of AMR β-lactamase towards a fast and accurate diagnosis.

Project description:Antibiotic resistance has become a serious threat to global public health and economic development. Rapid and accurate identification of a patient status for antimicrobial resistance (AMR) are urgently needed in clinical diagnosis. Here we describe the development of an assay method for activity fingerprinting of AMR β-lactamases using panels of 7 β-lactam antibiotics in 35 min. New Deli Metallo β-lactamase-1 (NDM-1) and penicillinase were demonstrated as two different classes of β-lactamases. The panel consisted of three classes of antibiotics, including: penicillins (penicillin G, piperacillin), cephalosporins (cefepime, ceftriaxone, cefazolin) and carbapenems (meropenem and imipenem). The assay employed a scheme combines the catalytic reaction of AMR β-lactamases on antibiotic substrates with a flow-injected thermometric biosensor that allows the direct detection of the heat generated from the enzymatic catalysis, and eliminates the need for custom substrates and multiple detection schemes. In order to differentiate classes of β-lactamases, characterization of the enzyme activity under different catalytic condition, such as, buffer composition, ion strength and pH were investigated. This assay could provide a tool for fast diagnosis of patient AMR status which makes possible for the future accurate treatment with selected antibiotics.

| S-EPMC10512244 | biostudies-literature

Variance-adjusted Mahalanobis (VAM): a fast and accurate method for cell-specific gene set scoring.

Project description:Statistical analysis of single cell RNA-sequencing (scRNA-seq) data is hindered by high levels of technical noise and inflated zero counts. One promising approach for addressing these challenges is gene set testing, or pathway analysis, which can mitigate sparsity and noise, and improve interpretation and power, by aggregating expression data to the pathway level. Unfortunately, methods optimized for bulk transcriptomics perform poorly on scRNA-seq data and progress on single cell-specific techniques has been limited. Importantly, no existing methods support cell-level gene set inference. To address this challenge, we developed a new gene set testing method, Variance-adjusted Mahalanobis (VAM), that integrates with the Seurat framework and can accommodate the technical noise, sparsity and large sample sizes characteristic of scRNA-seq data. The VAM method computes cell-specific pathway scores to transform a cell-by-gene matrix into a cell-by-pathway matrix that can be used for both data visualization and statistical enrichment analysis. Because the distribution of these scores under the null of uncorrelated technical noise has an accurate gamma approximation, both population and cell-level inference is supported. As demonstrated using simulated and real scRNA-seq data, the VAM method provides superior classification accuracy at a lower computation cost relative to existing single sample gene set testing approaches.

| S-EPMC7498348 | biostudies-literature

AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking.

Project description:Water plays a significant role in the binding process between protein and ligand. However, the thermodynamics of water molecules are often underestimated, or even ignored, in protein-ligand docking. Usually, the free energies of active-site water molecules are substantially different from those of waters in the bulk region. The binding of a ligand to a protein causes a displacement of these waters from an active site to bulk, and this displacement process substantially contributes to the free energy change of protein-ligand binding. The free energy of active-site water molecules can be calculated by grid inhomogeneous solvation theory (GIST), using molecular dynamics (MD) and the trajectory of a target protein and water molecules. Here, we show a case study of the combination of GIST and a docking program and discuss the effectiveness of the displacing gain of unfavorable water in protein-ligand docking. We combined the GIST-based desolvation function with the scoring function of AutoDock4, which is called AutoDock-GIST. The proposed scoring function was assessed employing 51 ligands of coagulation factor Xa (FXa), and results showed that both scoring accuracy and docking success rate were improved. We also evaluated virtual screening performance of AutoDock-GIST using FXa ligands in the directory of useful decoys-enhanced (DUD-E), thus finding that the displacing gain of unfavorable water is effective for a successful docking campaign.

| S-EPMC6274120 | biostudies-literature

Paving the Way Towards Universal Chimeric Antigen Receptor Therapy in Cancer Treatment: Current Landscape and Progress.

Project description:Chimeric antigen receptor (CAR) therapy has been proved effective in a stream of clinical trials, especially in hematologic malignancies. However, current CAR therapy is highly personalized as cells used are derived from patients themselves, which can be costly, time-consuming, and sometimes fails to achieve optimal therapeutic results due to poor quality/quantity of patient-derived cells. On the contrary, universal CAR therapy, which is based on healthy individuals' cells, circumvents several limitations of current autologous CAR therapy. To achieve the universality of CAR therapy, the allogeneic cell transplantation related issues, such as graft-versus-host disease (GVHD) and host-versus-graft activities (HVGA), must be addressed. In this review, we focus on current progress regarding GVHD and HVGA in the universal CAR therapy, followed by a universal CAR design that may be applied to allogeneic cells and a summary of key clinical trials in this field. This review may provide valuable insights into the future design of universal CAR products.

| S-EPMC7758418 | biostudies-literature

Hepatitis C eradication: A long way to go.

Project description:Hepatitis C virus (HCV) is a major global health problem with high morbidity and mortality. About 185 million people are living with HCV, of which 80% are living in low and middle income countries. With the development of new highly effective treatments for HCV, it is considered that the eradication of HCV may only be one step away. The major problem with new treatment options is its high price. The price of sofosbuvir-based treatment for one patient in the United States is US$85000-110000, while the actual production cost of a 12 wk direct-acting antiviral regimen is less than US$250. Another major hindrance in HCV eradication is the lack of quality management of blood transfusion screens. Due to the lack of HCV screening, 75% of people in the United States with HCV infection are unaware of their positive HCV status. The control of massive HCV pandemic will require a significant financial investment, political will, and support from medical, pharmaceutical, and civil organizations around the globe.

| S-EPMC4649134 | biostudies-literature

T Cell Immunity against Influenza: The Long Way from Animal Models Towards a Real-Life Universal Flu Vaccine.

Project description:Current flu vaccines rely on the induction of strain-specific neutralizing antibodies, which leaves the population vulnerable to drifted seasonal or newly emerged pandemic strains. Therefore, universal flu vaccine approaches that induce broad immunity against conserved parts of influenza have top priority in research. Cross-reactive T cell responses, especially tissue-resident memory T cells in the respiratory tract, provide efficient heterologous immunity, and must therefore be a key component of universal flu vaccines. Here, we review recent findings about T cell-based flu immunity, with an emphasis on tissue-resident memory T cells in the respiratory tract of humans and different animal models. Furthermore, we provide an update on preclinical and clinical studies evaluating T cell-evoking flu vaccines, and discuss the implementation of T cell immunity in real-life vaccine policies.

| S-EPMC7911237 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data